(1) Field of Invention
The present invention relates to a system for automatic detection of elevated structures and, more particularly, to a system for automatic detection of elevated structures in three-dimensional Light Detection and Ranging (LIDAR) point clouds.
(2) Description of Related Art
Light Detection and Ranging (LIDAR) is an optical remote sensing technology that can measure the distance to (or other properties of) a target by illuminating the target with light, typically using pulses from a laser. The ability to automatically detect and recognize elevated physical structures, such as bridges and overpasses, has many applications, including surveillance of a region and mission planning. Some of the current approaches for detecting elevated structures are based on explicit geometrical features and finite state cueing machines.
A geometric bridge detection algorithm proposed by Sithole and Vosselman in “Bridge detection in airborne laser scanner data”, in International Society for Photogrammetry and Remote Sensing (ISPRS) Journal of Photogrammetry and Remote Sensing, Volume 61, Issue 1, October 2006, 33-46 is based on the idea that features can be detected in a landscape based on cross-sections (i.e., profiles) in a landscape. The topological information contained in the cross-sections is used to identify seed bridge points. The seed bridge points are then used to detect individual bridges.
In another reference, Meng et al. in “Ground Filtering Algorithms for Airborne LiDAR Data: A Review of Critical Issues” in Remote Sensing 2010, 2, 833-860 use a multi-directional Ground Filter (MGF) for bridge detection. The reference indicates that, for certain filters (e.g., one-dimensional scanning filters), bridges may cause difficulty because they are smoothly connected with ground surfaces.
The approaches described above are based on explicit geometrical features and finite state cueing machines that do not provide adequate detection accuracy. These approaches produce significant rates of miss detections and false alarms. Thus, a continuing need exists for a system for automatic detection of elevated structures that is not based on explicit geometrical features and provides better detection accuracy than the prior art.